Determining the Precision of Spectral Patterns Arising from Atmospheric Correction Utilizing MODTRAN-FLAASH and 6S Approaches on High-Resolution SPOT-6 Imagery

High-resolution SPOT-6 imagery plays a crucial role in spatial and regional analysis, as well as land monitoring. However, atmospheric disturbances in scene images lead to suboptimal information extraction. Hence, the atmospheric correction process is essential during the initial processing of SPOT images. Unfortunately, the atmospheric correction of high-resolution images has not been extensively studied. In this paper, we compare the accuracy of the radiation transfer model technique by assessing the MODTRAN-FLAASH and 6S algorithms on high-resolution SPOT-6 images within Semarang city. RMSE values from both algorithms are calculated for nine different objects: grass, red floor tiles, granite tiles, brick tiles, paving blocks, marble, water, mangroves, and garbage piles. The RMSE values obtained from the MODTRAN-FLAASH and 6S methods are nearly identical for each object. Based on the average RMSE value, it is evident that the MODTRAN-FLAASH algorithm yields a lower average RMSE value than the 6S algorithm. Consequently, the MODTRAN-FLAASH approach is recommended for the SPOT image atmospheric correction process.